Treadmill training device adapted to provide targeted resistance to leg movement

ABSTRACT

A system and method are provided for targeted training of a person walking on a powered backward moving surface. Kinematic information of motor performance, such as ankle position and velocity, is measured throughout one or more phases of a gait cycle with a detector. The gait phase is determined, and a resistive/assistive force is applied to the leg that differs depending upon the gait phase and the measured kinematic information.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application is a divisional of U.S. patent application Ser.No. 12/536,136, filed Aug. 5, 2009, now U.S. Pat. No. 9,713,439, whichclaims the benefit of U.S. Provisional Application No. 61/086,592, filedAug. 6, 2008, entitled, “TREADMILL TRAINING DEVICE ADAPTED TO PROVIDETARGETED RESISTANCE TO LEG MOVEMENT”, the entire content of all beingincorporated herein by reference.

BACKGROUND

The overall goal of the invention is to enhance independent walkingfunction in people with incomplete spinal cord injury (SCI), poststroke, and other similar injuries or conditions by minimizing theamount of walking assistance provided or by adding targeted resistanceto the legs during body weight supported treadmill training (BWSTT).Providing targeted resistance load based on the motor performance of thepatient improves the training outcomes of BWSTT through enhanced patienteffort that effectively engages adaptive sensorimotor processes.

Spinal Cord Injury

The estimated prevalence of SCI in the United State is approximately253,000 individuals. Approximately 52% of the people with SCI sufferfrom functionally incomplete spinal cord injury and could benefit fromgait retraining. With the emergence of new treatments such as cellimplants, the use of growth-stimulating factors and other technologies,the number of people with SCI needing gait retraining is likely toincrease even further.

One of the most common goals of patients with SCI is regaining walkingability, as limitations in mobility can affect most activities of dailyliving. Following an SCI, descending spinal pathways are damaged. Theloss of descending input to spinal neurons may reduce synaptic drive tolocomotor networks and also compromise the ability to produce voluntarymovements of the limbs. As a result, an obvious consequence of SCI isparalysis, or weakness of lower extremity muscles that may have asubstantial adverse impact on walking.

Individuals with SCI may suffer difficulties supporting their bodyweight during the stance phase of gait or lifting and bringing the legforward during swing due to the muscular weakness associated with theinjury. As a consequence, people with SCI often require assistivedevices, such as a rolling walker, and spend more of the gait cycle indouble support (i.e., bearing weight in both legs to improve support).

In general, successful locomotor recovery following SCI depends on theavailability of residual descending commands and on maximizing neuralplasticity of spinal and supraspinal locomotor networks. The neuralreorganization achieved during rehabilitation is highly dependent on themagnitude and specificity of targeted neural activity. Thus, to maximizemotor recovery, the various embodiments of the present invention offerrehabilitation after neurological injury that emphasizes active,repetitive, task-specific practice that maximizes neuromuscularactivity.

Current BWSTT techniques are generally designed to improve motorfunction and ambulation in people with SCI. During such current BWSTT,the patient is given body weight support and assisted to move their legsin a “kinematically correct gait” by a physical therapist. This trainingparadigm largely meets criteria for effective neuroplasticity: thetraining is task-specific and utilizes both active and sensory pathwaysof the relevant neuromuscular systems.

Stroke

Stroke is currently the leading cause of disability in the U.S. withapproximately 1.1 million individuals currently with stroke-relateddisabilities. Impaired mobility is an important factor in determiningthe degree of physical disability after stroke. While up to 80% ofindividuals with stroke may ultimately recover the ability to walk shortdistance, most of them do not achieve the locomotor capacity necessaryfor community ambulation. Walking ability post-stroke is characterizedprimarily by reduced walking speed and endurance, residual spatial andtemporal left-right asymmetry, and impaired postural stability. Patientspost-stroke suffer a greatly reduced knee flexion at toe off and peakknee flexion during swing of the paralyzed leg compared to the intactleg, which is usually associated with compensation by pelvic hiking andlimb circumduction. The impaired hip and knee flexion during swing phasemay result in a decreased forward progression and velocity, shortenedstep length and toe drag at initial swing. These impairments restrictindependent mobility and severely impact post-stroke patients' qualityof life.

Decreased overground walking speed is a result of decreased cadence,decreased stride length and increased non-paretic single limb stanceduration. Mechanisms underlying reduced gait velocity are thought to bethe weakness of the paretic limb, particularly hip flexor andplantarflexor strength, spasticity, and the loss of inter- andintra-limb coordination. Rehabilitation efforts to improve strength andmuscle coordination patterns during hemiparetic gait may improve gaitvelocity and quality and therefore improve performance of activities ofdaily living.

To improve gait performance and functional outcomes followingneurological injury, rehabilitation efforts have been focused onre-establishing normal walking patterns. Towards this end, the use ofBWSTT has demonstrated significant improvement in walking capability inindividuals post-stroke. By providing a portion of body weight over atreadmill and manual facilitation from therapists, research hasdemonstrated improvements in temporal-spatial gait patterns, includinggait velocity, endurance, balance, and symmetry.

While statistically significant improvements in walking recovery withBWSTT have been shown, it remains unclear whether therapeutic effects ofsuch training are maximized. Specifically, in studies that have employedhigh intensity walking regimens in individuals with chronic stroke(i.e., those without presumed spontaneous recovery), the averageincrease in walking speed ranges have been achieved. These increasesequating to an increase of approximately 10% of healthy adult walkingspeed are small relative to the effort required to perform suchtraining. In addition, the major limitation of BWSTT is that it requiresgreater involvement of the physical therapist, i.e., generally two oreven more therapists are required in setting the paretic limb andcontrolling the trunk movement, and it is a labor intensive work forphysical therapists, particularly for those patients who requiresubstantial walking assistance following stroke. As a consequence, thereis a need to produce greater functional improvements in a larger patientpopulation.

Current Robotic Systems

Due to these limitations in BWSTT, several robotic systems have beendeveloped for automating locomotor training, such as the Lokomat gaittrainer (Colombo et al. “Treadmill Training of Paraplegic Patients Usinga Robotic Orthosis,” J. Rehabil Res. Dev. 37:693-700 (2000)) and theGait Trainer (GT) (Hesse et al. “A Mechanized Gait Trainer forRestoration of Gait,” J. Rehabil Res. Dev. 37:701-708 (2000)). TheLokomat gait trainer is a motorized exoskeleton that drives hip and kneemotion with a fixed trajectory using four DC motors, but it is difficultto back drive the Lokomat because it uses high-advantage, ball screwactuators. The Gait Trainers rigidly drive the patient's feet through astepping motion using a crank-and-rocker mechanism attached to footplatforms. These robotic systems had at their onset the basic designgoal of firmly assisting patients in producing correctly shaped andtimed locomotor movements.

This approach is effective in reducing therapist labor in locomotortraining and increasing the total duration of training but showsrelatively limited functional gains for some patients. For instance, intests, only 0.06 m/s gait speed improvement was obtained following 4weeks of training using a Lokomat. Especially, recent data indicate thatrobotic-assisted BWSTT is even less effective in improving walkingability in individuals post stroke than physical therapist-assistedlocomotor training. Such results suggest that currently availablerobotic-assisted BWSTT does not significantly help stroke patients orindividuals with SCI regain gait function so that their principalbenefit is in reducing the labor effort of the physical therapist.

The limited effectiveness of current robotic systems for locomotortraining may be due to the employment of the fixed trajectory controlstrategy. The algorithms that have been used in current availablerobotic systems for locomotor training have focused primarily onrepeated movements of the limbs via predefined, fixed-kinematictrajectories, although new control algorithms have been tested recently(Riener et al. “Patient—Cooperative Strategies for Robot-Aided TreadmillTraining: First Experimental Results,” IEEE Trans Neural Syst. Rehabil.Eng., 13:380-94 (2005)).

This type of training, however, eliminates cycle-to-cycle variation inthe kinematics of the leg, a fundamental feature of the natural neuralcontrol of repetitive movements such as stepping. Indeed, fixedkinematic trajectory may lead to a learned helplessness condition, inwhich patients have less self-controlled success in generating theappropriate stepping movement of the lower limbs. In addition, a roboticorthosis driven in a fixed pattern effectively limits the degrees offreedom of the leg motion as compared with naturally occurring muscleactivation patterns.

In contrast, the present inventors have determined that motor learningis more effective with a robotic algorithm that allows some variabilityin the stepping pattern than with a fixed trajectory paradigm. Thus, atraining algorithm that permits the intrinsic variability in theactivation of motor pools may allow the spinal circuits to exploremultiple patterns of activation and thereby optimize trainingeffectiveness. Thus, the system of the present invention does notprecisely control the trajectory of the leg, but rather allows patientsfreedom to volitionally move their legs during treadmill walking using anovel cable robotic system.

The resulting variations from step to step are believed to be animportant feature in motor learning in accordance with the presentinvention. There are many examples of tasks having some intrinsic levelof variation in both the biomechanics and the timing of the neuronsrecorded during the repetitive performance of the task. Stepping is anexcellent example of a motor task that is performed routinely andrepetitively, but even under the most controlled conditions on atreadmill, no two steps are identical. This intrinsic variation instepping is highly suggestive of a fundamental feature of the neuralcontrol of movement. It is already known that complete andstereologically constant assistance reduces the level of activation ofthe motor circuits that generate stepping. Thus, the system does notcontrol the kinematics of the lower limbs during stepping in a mannerthat produces minimal variation—a minimal variation results in poorerstepping ability than if some level of variation is allowed during thestepping.

Rather, variation in stepping can be retained during treadmill steppingby applying assistance as needed (AAN). An experienced therapist mayguide the patient to achieve a targeted motion trajectory, giving helponly when the patient exhibits a large deviation from some desiredtrajectory or has difficulty in performing the movement. By applyingAAN, the efficacy of BWSTT is improved by increasing patient effort andactive involvement in motor learning.

This is supported by observations that active motor training is moreeffective than passive training in eliciting performance improvement.Evidence from spinalized mice indicates that motor learning is moreeffective with AAN than with a fixed trajectory paradigm. In addition,therapist-assisted treadmill training using an AAN strategy facilitatesgreater improvements in walking ability in ambulatory stroke survivorsas compared to robotic-assisted training using a fixed trajectoryparadigm. Thus, applying a controlled load using an AAN strategyencourages the active involvement of the patient to enhance the trainingefficacy of robotic BWSTT.

For high functioning patients, an assistance only training paradigm maybe less effective than no assistance for improving walking ability.Thus, the present system applies an adaptive disturbance load to theparetic leg of ambulatory stroke patients to produce a deviation in stepkinematics, thereby improving the efficacy of BWSTT. This is supportedby results from arm training in patients post stroke. Specifically, datafrom hemiparetic subjects practicing upper limb movements with forcesthat provide passive guidance vs. error enhancement indicate thatgreater improvements in performance are achieved when errors aremagnified. These results indicate that causing adaptation by usingerror-augmentation training might be an effective way to promotefunctional motor recovery for patients with stroke.

In addition, results from locomotor training in healthy subjects showthat motor learning is accelerated by amplifying, rather than reducing,movement errors. Thus, applying a tolerated disturbance load to producekinematic deviations of the leg during treadmill training may acceleratethe motor learning during BWSTT in the patient following a stroke orspinal cord injury.

Motor adaptations driven by disturbance loading may produce‘aftereffects’ that improve stepping performance and eventually enhancetraining paradigms. In animal preparations, locomotor behavior can beconditioned to overcome an obstacle and the animal continues to stepwith an elevated trajectory on the removal of the obstacle. Thisaftereffect suggests a remodeling of locomotor patterns in anticipationof the perturbation. There is similar evidence from human experimentsshowing lasting modifications in response to sustained alterations inwalking conditions. Human infants and adult subjects adapt to theconstant presence of a disturbance to swing phase movements and showaftereffects upon removal of the disturbance.

There is also evidence for modifications in interlimb coordination aftera period of walking on a rotating disk or a split-belt treadmill. Thepresence of aftereffects after a period of training with a disturbanceimplies the formation or recalibration of the motor output for a giventask, suggesting that adaptive training might also prove useful duringgait rehabilitation. It is likely that these motor adaptation mechanismsare driven by kinematic deviations from a normal walking pattern, suchthat disturbances to the leg during stepping can be used to increase thedrive to the leg through a motor adaptation mechanism. These motoradaptations, which occur relatively rapidly, are likely to engage neuralpathways useful for enhancing longer-term (weeks) training. A durablelong-term adaptation may be a consequence of repeated exposures to rapidshort-term plasticity associated with a given dose of training.

SUMMARY

While BWSTT techniques have been shown to provide improvements inlocomotor ability, motor function and balance, an objective of variousembodiments of the present invention is to improve the efficacy of thetechnique by minimizing the amount of assistance provided, and allowingindependent walking practice. Thus, as described below, the inventionprovides minimal assistance, or even tolerated resistance to movementduring targeted phases of gait to enhance the training effects of BWSTT.

Various embodiments of the present invention can also make BWSTT betterfor SCI patients through increased patient effort (i.e., enhancingdescending drive) and/or by engaging adaptive sensorimotor processesthat are sensitive to errors in trajectory. The design also haspotential for long term transfer to overground gait following repeatedexposures.

Another goal is to improve the efficacy of BWSTT in people post strokeusing a novel robotic therapy that applies forces to the paralyzed legduring the swing phase of gait. Similar to treatment of SCI patients, acontrolled load is applied to the paralyzed leg at the ankle startingfrom late stance to mid swing through a novel, cable-driven actuatorwhile subjects walk on a treadmill. Providing assistance as needed (AAN)or resistance as tolerated (RAT), using a load based on the motorperformance of the patient improves the training outcomes of BWSTTthrough enhanced patient effort that effectively engages adaptivesensorimotor processes.

In assessing the motor adaptation to a disturbance (resistance) load inindividuals with, e.g., chronic (>6 month) stroke (or SCI>12 month) inaccordance with various embodiments of the invention, a controlledresistance load is applied to the paralyzed leg at the ankle, thigh, orother location during the early swing phase of gait (which is between atoe-off and heel-contact part of the gait) through a cable robot, whilethe subjects walk on a treadmill. The load is controlled andautomatically real-time adjusted based on kinematic performance tomaintain a stable stepping.

Partial body weight support may be provided to assure a stable steppingpattern on the treadmill while the treadmill speed is preferably set atthe maximum comfortable speed. The electromyography (EMG) from eightmuscles (tibialis anterior, soleus, medial gastrocnemius, vastusmedialis, rectus femoris, vastus lateralis, lateral hamstrings andmedial hamstrings) of each leg and the kinematics of the lowerextremities may be recorded to quantify the motor adaptive effects ofthe applied loads. Silver/silver chloride electrodes may be applied tolightly abraded skin over the belly of each muscle, and shielded leadswill be attached to a preamplifier/filter system (amplification 1000×,band-pass filter at 20-400 Hz). All signals should be electricallyisolated, amplified, filtered (400 Hz low pass) and sampled at 500 Hzusing a data acquisition board (National Instruments) on a PC withcustom LabVIEW (National Instruments, Austin, Tex.) software.

Leg muscle activity and limb kinematics adapt to the applied loads andshow aftereffects when removed. Specifically, enhanced flexor muscleactivities are produced in the lower limbs during adaptation to thetargeted perturbation and enhanced kinematics, such as increased stepheight and stride length, following the removal of disturbance load.Further, the enhanced kinematics carry over to overground walking.Locomotor recovery may be assessed using a resistance astolerated/assistance as needed strategy to control the load applied tothe paralyzed leg during BWSTT.

Using the resistance as tolerated/assistance as needed strategy improvesBWSTT in patients post stroke (and in patients with SCI). In addition,the control algorithm optimizes the amount of the applied load based onthe ongoing motor performance of the patient during training, therebyimproving gait in individuals post stroke or with SCI throughrobotic-assisted BWSTT.

While in most cases motor adaptation and associated aftereffects areshort-lived, the phenomenon has the potential for clinically significantchanges following repeated exposure. While limited studies havedemonstrated a long term (weeks) retention of motor adaptation usingrepeated measures, results from the use of the present system indicate asignificant cumulative effect consisting of the increased gait speed andstep length of the paralyzed leg following repeated exposure toresistance load training after two weeks training for six sessions.Thus, the motor adaptation to disturbance load and the after-effects canbe utilized to improve the motor performance of gait following therepeated exposure of the intervention in individuals post-stroke.

According to various embodiments of the invention, walking function isenhanced in people with incomplete SCI or post stroke by adding targetedresistance in order to increase patient effort and augment motoradaptation. Targeted resistance improves BWSTT through increased patienteffort and by engaging adaptive sensorimotor processes, especially forhigher-functioning patients. In addition, using an AAN/RAT strategy inrobotic locomotor training significantly increases the efficiency ofrobotic treadmill training. Various embodiments of the present inventionprovide a targeted resistance load as tolerated instead of persistentassistance to increase patient effort and further improve the efficacyof BWSTT by engaging adaptive sensorimotor process. Finally, the use ofan AAN/RAT strategy in robotic locomotor training improves functionaloutcomes in patients with incomplete SCI or post stroke to a greaterextent than previously-used assistance training paradigms.

One feature of this new system is that the trajectory of the gaitpattern is not fixed as it is for a crank-and-rocker mechanism, as usedin Gait Trainer (Hesse and Uhlenbrock 2000), but is flexible to allowpatients to produce a natural dynamic stepping trajectory. Thus, thepresent system does not precisely control the trajectory of the leg, butrather, controls the load applied to the leg during treadmill walkingusing a novel cable robotic system.

In addition, it is highly back-drivable, i.e., a human subject canperform a user-driven movement in the workspace with minimal opposition.The high backdrivability of the current system may be achieved by usingmotor directly driven cable spool and a light weight cable driven toapply controlled force to the leg (rather than a controlled trajectory).This feature has advantages over the ball-screw mechanisms used for theLokomat (Colombo et al. 2000), allowing patients to make and correcterrors across steps. The current system is highly backdrivable,compliant and allows freedom for patients to voluntarily move their legsduring BWSTT.

Accordingly a system is described herein for providing targeted trainingto a walking person, comprising: a powered backward moving surface thatthe person walks on; a force-applying element affixed to a leg of theperson; a gait phase detector; at least one of a leg portion positionsensor and a leg portion velocity sensor; a motor connected to theforce-applying element; and a controller comprising: an input connectedto the gait phase detector; an input connected to the leg portionposition or leg portion velocity sensor; an output connected to themotor; and an algorithm that accepts values related to a gate phase fromthe gait phase detector, to the leg portion position or leg portionvelocity and outputs a value related to a resistive force of the motorapplied to the force-applying element based on the gait phase.

An associated method is described for providing targeted training to aperson walking on a powered backward moving surface, comprising:measuring kinematic information of motor performance of a leg of theperson throughout one or more phases of a gait cycle with a detector;determining a phase of the gait; and applying a resistive force to theleg that differs depending upon the gait phase. A computer programproduct is also provided, comprising a computer usable medium having acomputer readable program code embodied therein, the computer readableprogram code adapted to be executed to implement the method.

DESCRIPTION OF THE DRAWINGS

The invention is described below with reference to various embodimentsillustrated in the drawings and following description.

FIG. 1A is a pictorial diagram of an embodiment of the treadmilltraining device;

FIG. 1B is a block diagram of an embodiment of the controller;

FIG. 1C is a flowchart illustrating basic steps in an exemplary methodembodiment;

FIG. 2 is a graph showing a kinematic measure of the person's leg afterthe resistance treatment;

FIG. 3 is a graph showing an exemplary assistance force applied to theleg of one subject post stroke during treadmill training;

FIG. 4A is a graph showing the average step height of three strides atthe baseline (before loading) and post load release for resistance loadtraining;

FIG. 4B is a graph showing the average stride length of three strides atthe baseline (before loading) and post load release for resistance loadtraining;

FIG. 5A is a graph showing the average step height of three strides atthe baseline (before loading) and post load release for assistance loadtraining;

FIG. 5B is a graph showing the average stride length of three strides atthe baseline (before loading) and post load release for assistance loadtraining;

FIG. 6 is a graph illustrating an improvement in overground walkingspeed after receiving the trajectory fixed robotic-assisted BWSTT.

FIG. 7A is a graph plotting a stride-by-stride of step length of aparalyzed leg (from one individual post stroke), showing average valuesfor three steps for a resistive load;

FIG. 7B is a graph plotting a stride-by-stride of step length of aparalyzed leg (from one individual post stroke), showing average valuesfor three steps for an assistive load;

FIG. 8A is a graph showing the average step height of five steps at thebaseline (before loading) and post load release for resistance loadtraining;

FIG. 8B is a graph showing the average stride length of five strides atthe baseline (before loading) and post load release for resistance loadtraining;

FIG. 9A is a graph showing plots related to the step length of paralyzedleg during overground walking prior to and 10, 20 and 30 minutes postresistance load training;

FIG. 9B is a graph showing plots related to overground gait speed priorto and 30 minutes post resistance load training;

FIG. 10A is a graph showing overground gait speed of an individual poststroke following repeated exposure of resistance load training, with thevalues being average values of three trials for each condition;

FIG. 10B is a graph showing step length of the paralyzed leg followingrepeated exposure of resistance load training, with the values beingaverage values of three trials for each condition;

DETAILED DESCRIPTION OF THE EMBODIMENTS Physical System

The novel cable driven system/robot 10, according to an embodiment ofthe invention as illustrated in FIG. 1A, has been developed to aid aperson 12 undergoing therapy to provide assistance/resistance load tothe person's legs at the ankle or above the knee during locomotortraining.

Assistance or resistance of an amount calculated by a computer algorithmin a controller is provided to the legs of a person walking on a poweredbackward moving surface, such as a treadmill, at a specific phase of thegait cycle in order to maintain a stable stepping. In order to encouragean active training, and given exhaustion by the person, the load must bevaried over time.

As can be seen in the embodiment illustrated in FIG. 1A, holdingelements, such as custom braces 20R, 20L (R and L designating right andleft—collectively element 20) or other holding elements are preferablystrapped to a lower thigh region or ankle of the person 12 to provideresistance or assistance load during the swing phase of locomotion,although other leg attachment points (shin, upper thigh) couldpotentially be used as well.

The braces 20 are connected to a drive system 40 via connecting elements50RF, 50RR, 50LF, 50LR (R and L designating right and left, F and Rdesignating front and rear—collectively element 50) serving asforce-applying elements that, in a preferred embodiment, comprise fournylon-coated stainless-steel cables (1.6 mm diameter), driven by fourmotors 42RF, 42RR, 42LF, 42LR (collectively element 42) (AKM33H,Kollmorgen, Drive amplifier, Servostar 30661) through four cable spools44RF, 44RR, 44LF, 44LR (collectively element 44) and pulleys 45RF, 45RR,45LF, 45LR (collectively element 45), the cables 50 being affixed tocustom braces 20. Other types of movement actuators, including rigidmembers such as bars, could also be used—and in this case, only one perbrace need be used. One spool per cable as a part of the movementactuator is provided in the preferred embodiment, although an alternatedesign is to have both a front and rear cable for a given leg brace tobe wound on the same spool, in opposite directions so that an extensionof one (e.g., front) cable corresponds with a retraction of the other(e.g., rear) cable.

Four one-degree-of-freedom reaction torque load cells 46RF, 46RR, 46LF,46LR (collectively element 46) (TRT-200, Transducer Techniques,Temecula, Calif.) may be integrated between the output shafts of themotors 42 and the cable spools 44 to record applied torques, althoughother mechanisms for measuring applied force could be used. A pretensionforce of 2-3N may be applied to both the forward and reverse cables toprevent slack, assuring the other leg does not get snagged. A monitor 70may be set in front of the person 12 to provide visual feedback ofhis/her motor performance.

The operator can control the cable robot 10 at a high level via a userinterface that may be programmed in, e.g., LabVIEW (NationalInstruments, Austin, Tex.), with personal safety ensured by a mechanicalstop, an accessible panic switch, and monitoring by a licensed physicaltherapist with knowledge of the cable robot 10 at all times during gaittraining. Side support may be provided using a group of springs 68attached to a torso harness 69 at the level of the pelvis.

The ankle trajectory signals may be measured using, e.g., a customdesigned 3-dimensional position detector. This comprises a detector barand two joints located at the two ends of the bar. At the lower end ofbar, it has a U-joint with 2 rotational degree of freedom (DOF) throughwhich the bar is attached to the ankle with a strap. At the upper end ofthe bar, it has a U-joint with 3 DOFs (1 linear and 2 rotational)through which the bar is attached to the frame located at the side ofthe treadmill. The rotation center of the U-joint at the upper end maybe adjusted to align with the hip joint to estimate the hip joint angle.Two potentiometers (P2201, Novotechnik, Southborough, Mass.) may be usedto measure the rotational angular position and 1 linear positiontransducer (SP-2, Celesco, Chatsworth, Calif.) may be used to measurethe linear position of the bar. Other mechanisms, such as imagingsystems, accelerometers, and the like could also be used as well. It isalso possible to measure any one of position, velocity, acceleration,and calculate the others from the measured values.

The horizontal position and velocity signals of the ankle may be used bythe operator to control the timing of loading and unloading, and todetermine a specific load amount to apply at each step. The horizontalvelocity of the ankle may be used as a trigger to start loading from thelate stance to mid swing. The amount of the load will be real-timecalculated by comparing the difference between the normalized anklehorizontal position and velocity and the measured values. The positionand velocity gains may be determined at the beginning of the trainingand depend on the tolerance of each subject.

Although other delineations of gait phase may be utilized, the gaitphases can generally be broken down into a post-heel-contact phase, apre-toe-off phase, a post-toe-off phase, and a pre-heel-contact phase.

Subjects may utilize a counterbalancing system 60 and be fitted with anoverhead harness 61 attached to a pulley 62/counterweight 63 supportsystem. The counterweight 63 can be adjusted, e.g., via a winch 64 tosupport from 0 to 100% of the person's 12 body weight during treadmillstepping. The person 12 should wear comfortable shoes and walk on atreadmill 55 (Woodway, Waukesha, Wis.) at their maximum comfortablevelocity.

In sum, as illustrated in FIG. 1A, the motor driven cable apparatus withbody weight support system 10 comprises four cables 50 driven by fourmotors 42, pulleys, and cable spools 42 are used to applyresistance/assistance load during the swing phase of walking. A personalcomputer, as a controller 100, may comprise algorithms that acceptinformation provided to the computer related to the motor performance ofthe person as they are walking on the treadmill, and calculate an amountof force that is to be applied to the legs of the person.

Controller

As illustrated in FIG. 1B, the controller 100 is designed toautomatically adjust the amount of assistance or resistance provided bythe cable robot 10 based on the motor performance of the person 12. Theadaptive control algorithm uses an assistance as needed/resistance astolerated (AAN/RAT) strategy. For example, to determine the appropriateamount of resistance to forward motion of the leg during a phase of thegait, which is determined by gait phase inputs 110, it is desirable toresist the leg movement without dramatically disrupting the overallkinematic pattern of walking. Toward this end, motor performance forthis task is quantified using kinematic information from the legs 120,and resistance or assistance commands 130 are provided to the motorcontrol as determined.

The controller automatically adjusts the load provided by the cables,based on the kinematic performance of the subject. The control algorithmcan be designed for an assistance or resistance strategy. The load maybe applied starting at pre-swing (10% gait cycle prior to toe off)through mid-swing of gait on the paretic leg. For the assistanceparadigm, the assistance force provided is proportional to the kinematicerror during the swing phase. Specifically, the force applied to thelegs is determined using the following equation:

F _(a)(t)=−k _(P)(x(t)−x _(d)(t))−k _(D)({dot over (x)}(t)−{dot over(x)} _(d)(t))  (1)

where

-   -   T is time;    -   F_(a)(t) is the applied assistive force as a function of time;    -   k_(P) is a subject- and session-specific position gain; its        value is determined at the beginning of each training session        and depends on the tolerance of each subject. A larger value of        k_(P) represents a larger force to be applied to the leg for a        given ankle position error, i.e., the difference between the        measured position value and normalized value obtained from        healthy subject;    -   k_(D) is a subject- and session-specific velocity gain; the        value is determined at the beginning of each training session. A        larger value of k_(D) represents a larger force to be applied to        the leg for a given ankle velocity error, i.e., the difference        between the measured ankle velocity and normalized values        obtained from healthy subject;    -   x(t) is the measured ankle horizontal position during the swing        phase;    -   {dot over (x)}(t) is the measured ankle horizontal velocity        during the swing phase;    -   x_(d)(t) is the desired ankle horizontal position during the        swing phase; and    -   {dot over (x)}_(d)(t) is the desired ankle horizontal velocity        during the swing phase;

The desired positions and velocities are determined from the meanrecorded the ankle trajectory using the position sensor for two healthysubjects walking on the treadmill. These position and velocity signalsare then normalized via interpolation using a cubic spline to the meanstep duration. The assistance force applied to the leg of one subjectpost stroke during treadmill training is shown in FIG. 3.

This Figure shows the assistance force produced by the cable robot andankle horizontal position of one subject following chronic stroke(female, left-side paretic weakness, 38 years old and 28 months poststroke) during treadmill walking. The subject walked on a treadmill withtheir maximal comfort speed, set at 1.7 kmph. No body weight supportedwas provided but a harness was used for safety only.

For the condition with resistance training, it is desirable to resistthe leg without dramatically disrupting the overall kinematic pattern ofwalking. Toward this end, the controller is designed to provide aresistance force such that if the kinematic error is too large, theresistance force decreases. However, if the kinematic error is small(more close to the normal pattern), the resistance force increases tomaintain some level of error. Specifically, the resistance force appliedto the leg is determined using the following equation:

F _(r)(t)=k _(P)(e _(t)−(x _(d)(t)−x(t)))+k _(D)(ė _(t)−({dot over (x)}_(d)(t)−{dot over (x)}(t)))  (2)

where

-   -   e_(t) is the preset threshold value for the position errors:        e_(t)=280 mm nominal; and    -   ė_(r) is the preset threshold value for the velocity errors:        e_(t)=25 mm/s nominal.    -   F_(r)(t) is the applied resistive force as a function of time;

FIG. 1C is a basic flow chart 200 highlighting the primary processsteps. A leg brace is affixed to the leg at some position 210,preferably the ankle or lower thigh. A force-applying element isattached to the leg brace 220, which could include a bar, cable, or anyother connecting element capable of providing a moving force to thebrace. A gait phase is determined 230, and at the proper gait phase, aforce is applied.

In addition, a monitor 70 may be set in front of the person 12 toprovide visual feedback about motor performance using, e.g., two barswith different color and height, and the ankle trajectory. Specifically,two bar graphs can be displayed on the screen to indicate the kinematicperformance of two legs. This feedback as an adjunct to provide themotivation to the person 12 for further improving their performancethroughout the course of the training.

Studies and Results

Study 1

To assess the impact of targeted resistance load on the locomotion inindividuals with SCI, one subject with incomplete spinal cord injury(Male, 45 years old, injury level at C5, the time post injury was 37months and American Spinal Cord Association (ASIA) classification D) wasinvited to participate in a pilot study. The patient's scores on theWalking Index for Spinal Cord Injury II (WISCI II) was 16/20. The scoreon the Lower-Extremity Motor Score (LEMS) was 50/50, and the 10-Meterwalking speed was 0.51 m/s. The subject was fitted into an overhead bodyweight support system through a harness (for safety only and no bodyweight was supported) and walked on a treadmill with the speed set at1.8 kmph. A cable was attached to the right leg at the ankle using astrap, which was then connected to the cable spool to provide a constantresistance (backward) or assistance (forward) load to the lower leg. Theloads applied to the legs were controlled through a PC using custom LabVIEW software.

Two types of loads, resistance and assistance, were applied to the rightleg through the cable, with a 10 minute interval between the applicationof the loads to allow washout of any lingering aftereffects. A constantload, 5 N for the first 20 steps, 15 N afterwards, was applied to theankle through the cable-driven system according to an embodiment of theinvention for the purpose of the pilot test. For each test run, thesubject walked on the treadmill without load for 2 minutes, defined asthe baseline period, and then a resistance or assistance load wasapplied to the leg for 5 minutes, defined as the adaptation period, andafter that, the load was removed and the subject continued to walk onthe treadmill for another 1 minute, defined as the post-adaptationperiod.

Surface EMG data from 6 muscles of the right leg were recorded usingactive Delsys electrodes (model De 2.1, Delsys Inc., Boston, Mass.).Kinematic data from the hip, knee and ankle were recorded using threeelectrogoniometers (Biometrics, Inc, UK) attached at the hip, knee andankle. The length of the lower leg, measured between the ankle and kneeaxes of rotation and the length of the femur were measured forsubsequent calculations of the step height and stride length. All datawere sampled at 1000 Hz using a data acquisition card (NationalInstruments, Austin, Tex.). Data were recorded starting from 1 minuteprior to the load application to 1 minute after the load was released.After 10 minutes rest, the test run was repeated using assistance load.The step height and stride length were calculated using the hip and kneejoint angle signals and the length of lower limb.

The load resistance and assistance tests appeared to have differenteffects on gait kinematics, measured using step height and stride lengthof the right leg. Providing resistance during the swing phase of gaitenhanced the training effects through increased patient effort, and anaftereffect consisting of increased step height and stride lengthfollowing the load release was observed, as shown at FIG. 2B.

Interestingly, the subject even overcompensated for the resistance loadduring the initial loading period (see FIG. 2B). To identify thetraining effect of resistance loads, the average step height and stridelength during the baseline (3 strides right before loading), and the 3strides following load release were calculated. Following 5 minutes ofresistance training, both the step height and stride length wereincreased with a more significant increase for step height (see FIGS. 4Aand 4B). In addition, the feedback from the subject was extremelypositive. He felt his trained leg (right leg) was much lighter followingthe resistance load training and wanted to participate in a futuretraining protocol.

Thus, FIG. 2B is a graph showing a stride by stride plot of step heightfor one subject with incomplete SCI. A constant resistance load wasapplied to the ankle through a custom strap using the cable drivensystem 10. As a safety precaution, 5N load was applied first and thenthe load was increased to 15N. The resistance load was releasedfollowing 5 minutes training on the treadmill.

FIGS. 4A and 4B are graphs showing the average step height, (FIG. 4A),and stride length, (FIG. 4B), of three strides at the baseline (beforeloading) and post load release for resistance load training. A constantresistance load (15N) was applied at the ankle through the cable drivensystem during the swing phase of the gait. The error bar indicates thestandard deviation of the step height and stride length of threestrides.

In contrast, persistent assistance load applied to the ankle appeared toreduce the patient effort during treadmill stepping. Following 5 minuteswalking with constant assistance (15N), the patient adapted to thisassistance perturbation, and demonstrated an aftereffect following theload release. In order to identify the training effect of assistanceloads, we calculated the average step height and stride length duringthe baseline (3 strides before loading), and the 3 strides followingload release.

As shown in FIGS. 5A and 5B, both the step height, FIG. 5A, and stridelength, FIG. 5B, were reduced after 5 minutes assistance load trainingon the treadmill, although larger differences were obtained for stepheight.

FIGS. 5A and 5B are graphs showing the average step height (FIG. 5A) andstride length (FIG. 5B), of three strides at the baseline (beforeloading) and post load release for assistance load training. A constantassistance load (15N) was applied at the ankle through a cable robot 10during the swing phase of the gait. The error bar indicates the standarddeviation of the step height and stride length of three strides.

Summary of Study 1

Results from this preliminary study indicated that providing targetedresistance to movement during the swing phase of the gait enhancedpatient effort, thereby enhancing the efficacy of BWSTT. In addition,following the release of a resistance load, there was a provenaftereffect, including increased step height and stride length, whichcould improve stepping. Such resistance training effects carry over tooverground stepping.

When using the cable driven system 10, the subject was allowed freedomto move his legs in a naturalistic stepping pattern instead of a fixed,standardized trajectory. This approach allowed variability in thekinematics of the stepping, allowed error in the stepping trajectory andmore closely mimicked the compliant assistance provided by a physicaltherapist compared to a fixed-trajectory motion typically provided byrobots in locomotor training. Using an AAN/RAT strategy in roboticlocomotor training, which mimics the assistance provided by physicaltherapists, enhanced the efficiency of robotic treadmill training to agreater extent than previously used assistance robotic trainingparadigms.

In summary, results from this preliminary test indicate that providingtargeted resistance to movement enhances the training effects of BWSTTthrough increased patient effort and by engaging adaptive sensorimotorprocesses.

Study 2

In this study, evidence was obtained that a subject post stroke adaptsto a swing resistance load applied to the paralyzed leg and shows an“after-effect” with the removal of the load. Further, the motoradaptation produced during treadmill training carried over to overgroundwalking with enhanced step length and gait speed following resistancetraining. In addition, a substantial increase of the overground gaitspeed was observed following two weeks of repeated exposure toresistance training, suggesting a potential clinical significance withprolonged (weeks) resistance training.

To assess the impact of resistance training on locomotion in individualspost stroke, one subject with chronic stroke (female, 22 months poststroke, left-side paretic weakness with an ankle-foot orthosis) wasrecruited to participate to this pilot study. A resistant load (10N) wasapplied to the ankle of the paralyzed leg through a cable robot 10during the swing phase of gait. Kinematic data from the hip and kneewere recorded using two electrogoniometers (Biometrics, Inc, UK)attached at the hip and knee. The length of the lower leg, measuredbetween the ankle and knee axes of rotation and the length of the femurwere measured for subsequent calculations of the step height and stridelength.

All data were sampled at 1000 Hz using a data acquisition card (NationalInstruments, Austin, Tex.). An aftereffect consisting of increased stepheight and stride length was observed following the load release after10 minutes (a short rest was allowed after first 5 minutes) treadmilltraining, as shown in FIGS. 7 and 8A and B. Results from pre- andpost-resistance load training indicated that both the step height andstride length increased, although a more significant increase wasobserved for step height (see FIG. 8A, 8B).

FIG. 7 is a stride-by-stride plot of step length of paralyzed leg forone subject following chronic stroke. Each point shown in the figure isthe average value of three steps. The subject was fitted into anoverhead body weight support system through a harness for safety onlyand no body weight support was provided. The subject walked on atreadmill with the speed set at 1.7 kph. A 10N resistance load wasapplied at the ankle of the paralyzed leg. Resistance load was releasedfollowing 10 minutes training on the treadmill.

FIGS. 8A and 8B are graphs illustrating the average step height andstride length of five steps at baseline (before loading) and post loadrelease for resistance load training, A, step height; B stride length. Aconstant resistance load (10N) was applied at the ankle through a cabledriven system during swing phase of the gait. The error bar indicatesthe standard deviation of the step height and stride length of fivesteps at the baseline and 10 minutes post training.

In order to test the carryover effect of the motor adaptation obtainedduring the treadmill training to overground walking, overground gaitparameters were measured in the same subject with chronic stroke(female, 37 years old and 22 months post stroke). Overground gait speedand step length of the paralyzed leg (self selected and fast walking)were measured at pre, 10, 20 and 30 minutes post training using aGaitMat II (E.Q. Inc, Chalfont, Pa.). Resistance load (10N) was appliedto the ankle of the paralyzed leg during BWSTT through a cable-robot.Following 20 minutes (short rest was allowed after first 10 minutestraining) resistance treadmill training, a substantial increase of steplength of the paralyzed leg and the gait speed on the overground testwas observed for both self selected and fast walking at 10, 20 and 30minutes post training (see FIGS. 9A and 9B). These results suggest thatmotor adaptation produced during treadmill training might be transferredto overground locomotion and could be retained at least 30 minutes posttraining.

FIG. 9A is a graph showing plots related to an overground step length ofparalyzed leg of one subject post stroke (Female, 37 years old, 22months post stroke) prior to and 10, 20 and 30 minutes post resistanceload training. No body weight was support was actually provided, with anoverhead harness used for safety only. The treadmill speed was set at1.7 kmph. An ankle-foot orthosis and a single point cane were used bythe subject during overground walking.

FIG. 9B is a graph showing plots related to gait speed prior to and 30minutes post training. Three trials were tested for self selected andfast walking with the bar and error bar indicate the average and thestandard deviation of gait speed and step length of the paralyzed leg.

In order to test the prolonged retention of the motor adaptation toresistance load, a subject post chronic stroke was recruited toparticipate in this study. The study consisted of a two weeks (3 visitsper week) training protocol and one week follow up test. At each visit,the subject was trained on the treadmill for 20 minutes with aresistance load (10-11N) applied at the ankle of the paralyzed legthrough a cable robot. A short rest was allowed after 10 minutestraining. The treadmill speed was set at 1.7 kmph and no body weightsupport was provided, with an overhead harness used for safety only.Overground gait speed was measured at pre, 10, 20 and 30 minutes posttraining for subject self-selected and fast walking speeds using aGaitMat II (E.Q. Inc, Chalfont, Pa.). Three trials were recorded foreach condition.

Results indicated a significant accumulation effect of training onoverground gait speed following two weeks of repeated exposure toresistance load training. A substantial increase in gait speed wasobserved for self selected walking speed (increased from 0.69±0.01 m/sat baseline to 0.89±0.01 m/s post training, and 0.91±0.03 m/s at thefollow up) and fast walking (increased from 0.85±0.05 m/s at baseline to0.96±0.03 m/s post training, and 0.97±0.02 m/s at the follow up)following resistance load training using the cable driven system 10,FIG. 10A.

The improvement of self selected gait speed for this subject followingtwo weeks training was greater than the average values post four weeksBWSTT with assistance provided by a physical therapist (increment0.20±0.02 vs. 0.13±0.11 m/s) or a robotic system with fixed trajectory(increment 0.20±0.02 vs. 0.07±0.07 m/s), FIG. 6. The improvement of fastwalking gait speed for this subject is close to the average values withphysical therapist assisted treadmill training (increment 0.11±0.07 vs.0.13±0.11 m/s) but with less duration of training (6 vs. 12 sessions).In addition, the step length of the paralyzed leg was also increased forself selected and fast walking, indicating a prolonged retention ofmotor adaptation associated with repeated exposure to resistance loadtraining, FIG. 10B.

FIGS. 10A and 10B are graphs showing overground speed (FIG. 10A) andstep length of the paralyzed leg (FIG. 10B) of one subject post stroke(Female, 37 years old, 22 months post stroke, ankle-foot orthosis wasused at the paralyzed leg and a single point cane was used duringoverground walking) following repeated exposure of resistance loadtraining. The values indicated at the figures are the average values ofthree trials for each condition.

Summary of Study 2

In summary, results from this study indicate that a swing phaseresistance load enhances the training effects of BWSTT through increasedpatient effort and by engaging adaptive sensorimotor processes. Inaddition, repeated exposure of the resistance training may produceprolonged retention of the motor adaptation, suggesting a high potentialclinical significance of this training paradigm.

Thus, a person suffering from stroke or spinal cord injury can improvethe ability to walk by utilizing the inventive system that appliesresistance to the person's legs when walking on a treadmill. Resistanceof an amount calculated by a computer algorithm in a controller isprovided to the legs of a person on the treadmill at a specific phase ofthe gait cycle in order to maintain a stable stepping. In addition,given exhaustion by the person and locomotor recovery through out thecourse of training, the load must be varied over time.

The system or systems described herein may be implemented on any form ofcomputer or computers and the components may be implemented as dedicatedapplications or in client-server architectures, including a web-basedarchitecture, and can include functional programs, codes, and codesegments. Any of the computers may comprise a processor, a memory forstoring program data and executing it, a permanent storage such as adisk drive, a communications port for handling communications withexternal devices, and user interface devices, including a display,keyboard, mouse, etc. When software modules are involved, these softwaremodules may be stored as program instructions or computer readable codesexecutable on the processor on a computer-readable media such asread-only memory (ROM), random-access memory (RAM), CD-ROMs, magnetictapes, floppy disks, optical data storage devices, and carrier waves(such as data transmission through the Internet). The computer readablerecording medium can also be distributed over network coupled computersystems so that the computer readable code is stored and executed in adistributed fashion. This media can be read by the computer, stored inthe memory, and executed by the processor.

All references, including publications, patent applications, andpatents, cited herein are hereby incorporated by reference to the sameextent as if each reference were individually and specifically indicatedto be incorporated by reference and were set forth in its entiretyherein.

For the purposes of promoting an understanding of the principles of theinvention, reference has been made to the preferred embodimentsillustrated in the drawings, and specific language has been used todescribe these embodiments. However, no limitation of the scope of theinvention is intended by this specific language, and the inventionshould be construed to encompass all embodiments that would normallyoccur to one of ordinary skill in the art.

The present invention may be described in terms of functional blockcomponents and various processing steps. Such functional blocks may berealized by any number of hardware and/or software components configuredto perform the specified functions. For example, the present inventionmay employ various integrated circuit components, e.g., memory elements,processing elements, logic elements, look-up tables, and the like, whichmay carry out a variety of functions under the control of one or moremicroprocessors or other control devices. Similarly, where the elementsof the present invention are implemented using software programming orsoftware elements the invention may be implemented with any programmingor scripting language such as C, C++, Java, assembler, or the like, withthe various algorithms being implemented with any combination of datastructures, objects, processes, routines or other programming elements.Furthermore, the present invention could employ any number ofconventional techniques for electronics configuration, signal processingand/or control, data processing and the like. The words “mechanism” and“element” are used broadly and are not limited to mechanical or physicalembodiments, but can include software routines in conjunction withprocessors, etc.

The particular implementations shown and described herein areillustrative examples of the invention and are not intended to otherwiselimit the scope of the invention in any way. For the sake of brevity,conventional electronics, control systems, software development andother functional aspects of the systems (and components of theindividual operating components of the systems) may not be described indetail. Furthermore, the connecting lines, or connectors shown in thevarious figures presented are intended to represent exemplary functionalrelationships and/or physical or logical couplings between the variouselements. It should be noted that many alternative or additionalfunctional relationships, physical connections or logical connectionsmay be present in a practical device. Moreover, no item or component isessential to the practice of the invention unless the element isspecifically described as “essential” or “critical”.

The use of the terms “a” and “an” and “the” and similar referents in thecontext of describing the invention (especially in the context of thefollowing claims) are to be construed to cover both the singular and theplural. Furthermore, recitation of ranges of values herein are merelyintended to serve as a shorthand method of referring individually toeach separate value falling within the range, unless otherwise indicatedherein, and each separate value is incorporated into the specificationas if it were individually recited herein. Finally, the steps of allmethods described herein can be performed in any suitable order unlessotherwise indicated herein or otherwise clearly contradicted by context.The use of any and all examples, or exemplary language (e.g., “such as”)provided herein, is intended merely to better illuminate the inventionand does not pose a limitation on the scope of the invention unlessotherwise claimed.

Numerous modifications and adaptations will be readily apparent to thoseskilled in this art without departing from the spirit and scope of thepresent invention.

TABLE OF ACRONYMS

AAN assistance as needed

ASIA American Spinal Injury Association

BWSTT body weight supported treadmill training

EMG Electromyography

LEMS lower-extremity motor scoreRAT resistance as toleratedSCI spinal cord injuryWISCI walking index for spinal cord injury

TABLE OF REFERENCE CHARACTERS

-   R Right-   L Left-   F Front-   R Rear-   10 cable driven system/robot-   12 Person-   20 braces or holding element-   24 ankle position and/or velocity sensors-   40 drive system-   42 drive motors-   44 cable spools-   45 pulleys-   46 torque load cells-   50 connecting elements-   55 treadmill-   60 counterbalancing system-   61 overhead harness-   62 counterbalance pulley-   63 counterweight-   64 winch-   68 group of springs-   69 torso harness-   70 monitor-   80 static motor behavior measurement device-   82 motor-   84 main axial reaction torque transducer-   86 radial arm-   88 secondary axial reaction torque transducer-   90 foot clamp-   100 controller-   110 gait phase inputs-   120 step kinematic parameter inputs-   130 resistance or assistance commands-   140 target step kinematic parameters-   150 control algorithms-   200 method flowchart-   210-250 method steps

1-20. (canceled) 21: A system for providing targeted training to awalking person, comprising: a powered backward moving surface for theperson to walk on; a force-applying element for affixing to a leg of theperson; a gait phase detector; at least one of a leg portion positionsensor and a leg portion velocity sensor; a motor connected to theforce-applying element; and a controller comprising: an input connectedto the gait phase detector; an input connected to the leg portionposition or leg portion velocity sensor; an output connected to themotor; and an algorithm that accepts values related to a gait phase fromthe gait phase detector, to the leg portion position or leg portionvelocity and outputs a value related to a resistive force of the motorapplied to the force-applying element based on the gait phase. 22: Thesystem according to claim 21, wherein the force-applying elementcomprises: a holding element affixed to the leg of the person a frontcable attached to a front of the holding element; a rear cable attachedto a rear of the holding element; and one or more spools attached to themotor and comprising a part of the front and rear cables. 23: The systemaccording to claim 21, further comprising: a counterweight systemattached to the person for reducing a load on the legs of the personwhile walking on the powered backward moving surface. 24: The systemaccording to claim 21, further comprising: a feedback monitor visible tothe person comprising a display of parameters related to the motorperformance of the person. 25: The system according to claim 21, whereinthe controller comprises a processor having an algorithm that determinesa force applied to the force-applying element according to the followingequation:F _(r)(t)=k _(P)(e _(t)−(x _(d)(t)−x(t)))+k _(D)(ė _(t)−({dot over (x)}_(d) −{dot over (x)}(t))) where t is time; F_(r)(t) is the appliedresistive force as a function of time; k_(P) is the position gain (e.g.,k_(P)=0.1 N/mm nominal); k_(D) is the velocity gain (e.g., k_(D)=0.05N/mm/s nominal); x(t) is the measured ankle horizontal position duringthe swing phase; {dot over (x)}(t) is the measured ankle horizontalvelocity during the swing phase; x_(d)(t) is the desired anklehorizontal position during the swing phase; {dot over (x)}_(d)(t) is thedesired ankle horizontal velocity during the swing phase; e_(t) is thepreset threshold value for the position errors: e_(t)=280 mm nominal;and ė_(t) is the preset threshold value for the velocity errors:ė_(t)=25 mm/s nominal. 26: A computer program product, comprising acomputer usable medium having a computer readable program code embodiedtherein, said computer readable program code adapted to be executed toimplement a method for providing targeted training to a person walkingon a powered backward moving surface, the method comprising: measuringkinematic information of motor performance of a leg of the personthroughout one or more phases of a gait cycle with a detector;determining a phase of the gait; and applying a resistive force to theleg that differs depending upon the gait phase. 27: An apparatus forproviding targeted training to a person volitionally moving their legswhile walking on a powered backward moving surface, comprising: aholding element configured to receive a portion of a person's leg; adrive system; a cable attached to the holding element and to the drivesystem; at least one position detector that determines at least one ofthe horizontal position and horizontal velocity of a person's legthroughout one or more phases of a gait cycle to obtain kinematicinformation regarding motor performance of the leg; a controller that:determines a phase of the gait; and controls the drive system to, in aswing phase of the gait, apply a resistive force to the leg via thecable to resist a forward swing movement of the leg in an amount that isbased on the obtained kinematic information. 28: The apparatus of claim27, wherein the at least one position detector is one of a plurality ofthree dimensional detectors and the obtained kinematic information isankle horizontal position and horizontal velocity. 29: The apparatus ofclaim 28, wherein the controller carries out additional stepscomprising: determining and saving in a memory desired kinematicinformation comprising a desired measure of horizontal position as afunction of time or gait cycle (x_(d)(t)), and a desired measure ofhorizontal velocity as a function of time or gait cycle ({dot over(x)}_(d)(t)); and utilizing the obtained kinematic information and thedesired kinematic information in determining an amount of the resistiveforce that is applied to the leg. 30: The apparatus of claim 29, whereinthe controller carries out additional steps comprising: setting presetthreshold values for position errors e_(t) and velocity errors ė_(t)that are used in determining the amount of resistive force that isapplied to the leg. 31: The apparatus of claim 30, wherein the resistiveforce is applied to the leg according to the following equation:F _(r)(t)=k _(P)(e _(t)−(x _(d)(t)−x(t)))+k _(D)(ė _(t)−({dot over (x)}_(d)(t)−{dot over (x)}(t))) where t is time; F_(r)(t) is the appliedresistive force as a function of time; k_(P) is the position gain (e.g.,k_(P)=0.1 N/mm nominal); k_(D) is the velocity gain (e.g., k_(D)=0.05N/mm/s nominal); x(t) is the measured ankle horizontal position duringthe swing phase; {dot over (x)}(t) is the measured ankle horizontalvelocity during the swing phase; x_(d)(t) is the desired anklehorizontal position during the swing phase; {dot over (x)}_(d)(t) is thedesired ankle horizontal velocity during the swing phase; e_(t) is thepreset threshold value for the position errors: e_(t)=280 mm nominal;and ė_(t) is the preset threshold value for the velocity errors:ė_(t)=25 mm/s nominal. 32: The apparatus of claim 27, wherein the drivesystem comprises a motor and a cable spool, and the motor is arranged toactuate the cable spool. 33: The apparatus of claim 27, wherein thedrive system is positioned directly behind the leg during a therapysession 34: The apparatus of claim 27, further comprising a harness thatprovides side support to the patient. 35: The apparatus of claim 32,wherein the cable applies the resistive force by being wound around thecable spool during actuation of the motor. 36: The apparatus of claim27, further comprising a reaction torque cell that measures theresistive force. 37: The apparatus of claim 27, wherein the gait phaseduring which the resistive force is applied is only about 10% of thegait cycle prior to toe off through mid swing. 38: The apparatus ofclaim 27, wherein the controller performs further steps comprisingvarying the resistive force across gait cycles to maintain predefinedvalues for step kinematics. 39: The apparatus of claim 38, wherein thepredefined values for step kinematics include stride length and stepheight. 40: The apparatus of claim 27, further comprising ankle positiondetectors that determine an ankle position of the person, wherein thecontroller determines of the gait phase by reading information from theankle position detectors. 41: The apparatus of claim 27, wherein the atleast one position detector measures kinematic information of motorperformance by measuring EMG data from muscle groups associated with atleast one of hip, knee, and ankle muscles.